Impact of product market competition on real activity manipulation: Moderating role of managerial ability

In this study, we examine whether managerial ability moderates the association between product market competition and real earnings management. Prior literature largely supports the disciplinary effect of competition, suggesting that competition reduces real activity manipulation. We argue that this association is different depending on the level of managerial ability. Based on the reputation hypothesis, we argue that able managers negatively moderate the association between competition and real activity manipulation. Using a sample of US listed companies from 1997 to 2016, we find evidence to support our moderating assertion. A battery of robustness tests validates our original findings.     

Determinants and consequences of student satisfaction in Australian Universities: Evidence from QILT Surveys

We examine the determinants and consequences of student satisfaction, measured by satisfaction scores reported in the QILT surveys from 2012 to 2017. We find that university-level profitability determines overall student satisfaction, where a positive relationship exists between student satisfaction and university performance. This association is more pronounced for Group of Eight (Go8) universities and those with higher academic expenditure. These findings have important implications for higher education providers as the Australian Government is contemplating the use of QILT student satisfaction in allocating public funding for higher education.     

What drives customers toward proximity payment services? An integrated theory of planned behavior perspective

Proximity mobile payment (PMP) services facilitate mobile payments between payer and payee who are at same location thorough a proximity technology such as QR codes, Bluetooth, and near-field communication. It has potential to drastically change consumers' payment methods in developing countries where traditional finance infrastructure is lacking. However, there are various challenges to adopting PMP in such countries. This study aims to explore users' opinions on and motivations for using PMP by proposing an extended theory of planned behavior (TPB) model. It also seeks to resolve inconsistencies in PMP adoption studies regarding the role of user's trust in PMP services. A survey instrument was used to collect data from PMP users in a developing country. The data were analyzed using structural equation modeling. This study highlights trust as a mitigator of the negative effect induced by the perceived risk of using PMP services. It also validates that the TPB, coupled with other contextual factors, explains the adoption of PMP services in developing countries.     

On the Good and Bad of Natural Resource,Corruption, and Economic Growth Nexus

Environmental and Resource Economics - The empirical finding that countries endowed with vast reserves of natural resources are expected to experience slower economic growth – the resource...     

DETERMINANTS OF DEMAND FOR FIJI'S EXPORTS: AN EMPIRICAL INVESTIGATION

Fiji is no exceptin to the rule that exports are an important source of growth and development. In this light, it is important to know the determinants of exports. However, there is no empirical study on Fiji's export demand. This paper uses the modern econometric techniques—in particular, the autoregressive distributed lag approach to cointegration—to investigate whether the standard export demand variables, viz., trading partner income, export price, and competitor price, have a long‐run cointegration relationship with Fiji's real exports for the period 1970 to 1999. In addition, the long‐run results are also estimated by using the dynamic ordinary least squares and the fully modified ordinary least squares. The empirical results indicate the existence of a cointegration relationship among the variables. The long‐run foreign income, own‐price, and cross‐price elasticities are found to be 0.7 to 0.8, −1.3 to −1.5, and 2.1 to 2.2, respectively.     

Forecasting Commodity Market Returns Volatility: A Hybrid Ensemble Learning GARCH-LSTM based Approach

This study investigates the advantage of combining the forecasting abilities of multiple generalized autoregressive conditional heteroscedasticity (GARCH)-type models, such as the standard GARCH (GARCH), exponential GARCH (eGARCH), and threshold GARCH (tGARCH) models with advanced deep learning methods to predict the volatility of five important metals (nickel, copper, tin, lead, and gold) in the Indian commodity market. This paper proposes integrating the forecasts of one to three GARCH-type models into an ensemble learning-based hybrid long short-term memory (LSTM) model to forecast commodity price volatility. We further evaluate the forecasting performance of these models for standalone LSTM and GARCH-type models using the root mean squared error, mean absolute error, and mean fundamental percentage error. The results highlight that combining the information from the forecasts of multiple GARCH types into a hybrid LSTM model leads to superior volatility forecasting capability. The SET-LSTM, which represents the model that combines forecasts of the GARCH, eGARCH, and tGARCH into the LSTM hybrid, has shown the best overall results for all metals, barring a few exceptions. Moreover, the equivalence of forecasting accuracy is tested using the Diebold–Mariano and Wilcoxon signed-rank tests.     

Mergers and acquisitions research in finance and accounting: Past,present, and future

This study presents an analysis of publication patterns and major themes in research on mergers and acquisitions in finance and accounting. We find that takeovers as mechanisms of governance, drivers of mergers, mechanisms of mergers, bank mergers, cross-border mergers, shareholder wealth effects of mergers and related events, and the role of financial experts and ownership structure form major themes of research in the finance area, while in accounting area major themes are corporate governance and accounting outcomes, predicting takeovers and their outcomes, valuation, financial reporting and takeover decisions, and financial reporting and performance.     

How can banks and finance companies incorporate value chain factors in their risk management strategy? The case of agro-food firms

A value chain framework for guiding the financial firms in their credit decisions is urgent, as the current COVID-19 pandemic has highlighted, but missing in the extant literature, particularly for those that lend to industries sensitive to value and supply chain bottlenecks. This study creates knowledge in value chain finance, a big untapped and un-researched market. It constructs, confirms, and validates a value chain framework for assessing risks in lending to Agro and Food Processing firms in which value chain risks are major business concerns globally. To pursue the objectives of the study, we use a novel methodology that integrates the Modified Delphi technique, exploratory factor analysis, confirmatory factor analysis, and discriminant analysis. Based on testing and analysis of primary data, including loan data, a framework comprising six factors is proposed for use in conjunction with existing risk assessment models of finance companies to improve the quality of their credit decisions, contributing to their performance sustainability.     

Sovereign Bond Market Shock Spillover Over Different Maturities: A Journey from Normal to Covid-19 Period

Asia-Pacific Financial Markets - With application of Diebold and Yilmaz’s (Int J Forecast 28(1):57–66, 2012) spillover approach, we examine shock spillover in international sovereign...     

Benchmarking sustainable E-commerce enterprises based on evolving customer expectations amidst COVID-19 pandemic

The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e-commerce firms are also increasing globally. Thus, it has become crucial for an e-commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e-commerce enterprises based on evolving customer expectations due to the COVID-19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub-criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e-commerce firms. The results are obtained using a multi-criteria decision-making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision-making problem. Further, numerical analysis is conducted to evaluate and rank various e-commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub-criteria for e-commerce businesses to ensure customer expectations along with their economic and environmental sustainability.